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Record W7022697945

9781000541014.pdf

2021· other· en· W7022697945 on OpenAlexaboutno aff

Bibliographic record

VenueOAPEN (The OAPEN Foundation) · 2021
Typeother
Languageen
FieldEnergy
TopicGlobal Energy Security and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsGeopoliticsForeign policyInternational relationsGreenhouse gasPoliticsClimate changeEnergy policyEnergy securityGlobal warming
DOInot available

Abstract

fetched live from OpenAlex

Contributing to the emerging literature on the geopolitical and foreign policy implications of decarbonisation and energy transition processes, this book sheds light on the future of the European Union’s external relations under decarbonisation. Under the Paris Agreement on climate change, adopted in 2015, governments committed to phasing out the emissions of carbon dioxide and other greenhouse gases over the coming decades. This book addresses the many questions around this process of decarbonisation through detailed analyses of EU external relations with six fossil-fuel exporting countries: Nigeria, Indonesia, Azerbaijan, Colombia, Qatar and Canada. The authors systematically examine the six countries’ varying dependence on fossil fuels, the broader political and security context, current relations with the EU and the potential for developing these toward decarbonisation. In doing so, they put forward a series of findings that should hold across varying circumstances and provide a steppingstone to enrich and inspire further research on foreign policy, external relations and international relations under decarbonisation. The book also makes an important contribution to understanding the external implications of the 2019 European Green Deal. This volume will be of great interest to students and scholars of European environmental and climate policy, climate diplomacy, energy policy, foreign policy and climate/energy geopolitics.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.984
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.9750.952

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.262
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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